Enhancing Project-Based Blended Learning (PJBBL) Model in Algorithm Design: A Comprehensive Needs Analysis
Tao Lu
John Morris
Thanin Ratana-Olarn
This research explores the potential of Project-Based Learning (PBL) and the Cloud Education Model in Algorithm Design education. Through a multifaceted approach, the study identifies the specific needs of teachers and students when adopting the project-based learning model. In an experimental study, it used the PJBBL model in the domain of algorithm design education. A pre-test and post-test experimental design were used to reach a conclusion. Twenty teachers and 100 BS students were randomly selected from the college for interviews and questionnaire administration, respectively, whereas 66 students were selected through cluster sampling for experimentation. A pre-test-post-test design was used for the experiment, whereas descriptive statistics besides MANOVA were used to analyze the data. The study results indicate that the PJBBL model has shown promising outcomes in enhancing students' algorithm design and analysis capabilities. Integrating real-world projects and blended learning methods has deeply engaged students, fostering a better understanding of algorithmic concepts and their practical application. Teachers' feedback has shed light on effective pedagogical strategies, enabling them to create a conducive learning environment and support students in their algorithmic learning. The research demonstrates the efficacy of the Project-Based Blended Learning (PJBBL) model in Algorithm Design and Analysis education.
Keywords:Algorithm design, Project-based blended learning, Self-learning, Network engineering, Online project-based learning
